Phishing Predictor
Uses Two-class NN, Decision Jungle and Boosted trees to predict if a site is a phishing site or not. Dataset from UCI
I was browsing twitter and saw a tweet from Nicholas Papernot on how he created simple tutorial to classify phishing sites using the UCI dataset (It is awesome, and you should check it out. Link below)
I recreated his tutorial in Azure ML. I wanted fast and accurate learners, so I used Boosted trees, Decision Jungles and a simple two class Neural Network.
Accuracy Results:
-----------------
- Boosted Trees: 96.6%
- Decision Jungles: 94.3%
- Two class Neural Network: 95.9%
Reference
---------
1. Original Tutorial idea - @NicholasPapernot -
2. @NicholasPapernot awesome tutorial - [https://github.com/npapernot/phishing-detection][1]
3. Dataset Available at https://archive.ics.uci.edu/ml/datasets/Phishing+Websites
[1]: https://github.com/npapernot/phishing-detection